PHP Image Manipulation

Generate avatars with initials from user names.

Upload image using Laravel's build in function and resize it automatically.

🌄📐 A Laravel Nova advanced image field with cropping and resizing using Cropper.js and Intervention Image

Causal Inference with Invariant Prediction

On-demand image manipulation for WordPress via the Intervention Library.

VIPS driver for Intervention Image.

Explainability of Deep Learning Models

An annotated corpus of discussion forum threads from Massive Open Online Courses.

iReporter app enables users (citizen) to bring any form of corruption to the notice of appropriate authorities and the general public

Create colored avatars with letters in PHP

Image Uploading via laravel 5.7 framework with help of intervention and dropzonejs

Tu Ayuda en Tiempos de Crisis

Save images as static in real-time in different formats using Intervention Image.

Student database made with Laravel

Reports stuff that has happened on a particular day, based on the logs.

Describing and visualising baseline results of the Let's Move It intervention

Repository for systematic review of the literature on technological interventions to address reading skills

Predicting outcomes of educational interventions before investing in large-scale implementation efforts in school settings is essential for educational policy-making. However, due to time and resource limitations, conducting longitudinal, large-scale experiments testing outcomes of interventions in authentic settings is difficult. Here, we introduce the deep learning method as a way to address this issue and illustrate the use of the deep learning method for the prediction of intervention outcomes through a MATLAB implementation. The presented deep learning method extracts predictable patterns from an empirical dataset to simulate large-scale intervention outcomes. Findings from our simulations suggest that the deep learning applied simulation model can predict intervention outcomes significantly more accurately compared to the traditional regression analysis methods.

This is the Gplus project repository where we provide our code for fMRI and behavioural data analysing purposes. Functional data preprocessing is done with fmriprep. So far, we provide matlab code for importing fmriprep output in an SPM compatible format. 1st and 2nd level analyses scripts will follow as well as R code for the behavioural data analyses. For details, please visit our OSF project.

In this simulation, the intensity of the intervention is periodically varied over a period of time. Consider a case in which the government intervention issues a restraint or ban on going out and contact of people changes.